Video information generally deteriorates its quality when subjected to some process such as encoding or transmitting through a network. The degree of deterioration of such deteriorated video information sensed by a person who actually watches the deteriorated video information is called a subjective quality.
A conventional method of assessing a subjective quality carries out a subjective quality assessing test in which a human tester actually watches video images. Assessing a quality of video images by actually watching the video images with human eyes is laborious and takes a long time. In addition, persons skilled in the quality assessment and novices frequently provide different assessment results.
To solve the problems, there is a method of estimating a subjective quality of video images according to physical measurements. This method finds a difference between the physical feature values of a reference video signal and a deteriorated video signal, or obtains a deterioration quantity only from the physical feature values of the deteriorated video signal, and objectively assess a degree of video quality deterioration according to the difference or the deterioration quantity.
A subjective video quality may be accurately estimated from limited video images. (For example, ANSI T1.801.03-1996, “Digital Transport of One-Way Video Signals Parameters for Objective Performance Assessment”; Okamoto and Takahashi, “Study on application of video quality objective assessment technique,” IEICE society conference, September 2002; and Okamoto, Kurita, and Takahashi, “Study on improving the performance of video quality objective assessment,” IEICE society conference, March 2003 can be referred to.) The quality of a given video image is greatly dependent on the characteristics of the video image, and therefore, video images having the same degree of deterioration may be assessed to have different subjective qualities.
Due to this, technical situations still exist that require subjective assessment tests to be conducted by human testers actually monitoring video images and assessing the quality thereof.
In these situations, there has been proposed an objective assessment method (PCT Pub. No. WO99/45715) that assesses a subjective quality like a human assessor does. The method focuses on an edge area of a video image, applies a Sobel filter to a video signal, and calculates a deterioration quantity of the video image.
Feature values employed by this method, however, are insufficient to provide an assessment accuracy comparable to that of a subjective assessment by human.
For a method of estimating a subjective video quality by comparing the physical feature values of reference and deteriorated video signals with each other, there is a precondition that spatial and temporal positions must be aligned between the reference and deteriorated video signals. Namely, between the reference and deteriorated video signals, temporal and spatial deviations must be cancelled if any.
To achieve the alignment, a manual aligning process has been carried out. To cope with this, a technique of automatically carrying out the aligning process has been proposed. For example, U.S. Pat. No. 5,446,492 carries out, as a preprocess of an objective assessment, a temporal aligning process to solve delays if any.
This technique can establish and continuously maintain a synchronized state for signals having the same size and the same frame rate such as TV broadcasting signals.
Recent video signals, however, have various sizes and aspect ratios, such as signals used for video distribution and communication services provided through IP networks including the Internet and received at terminals, e.g., personal computers (PCs). These services involve a risk of losing information pieces such as packets. It is difficult, therefore, to align spatial positions between a reference video signal and a deteriorated video signal. If IP packet arrival intervals vary or if packets are lost, video display timing will shift, fluctuate, or freeze. This sort of phenomena has not been present previously, and therefore, there is no technique to correct a temporal deviation between a reference video signal and a deteriorated video signal.
If spatial and temporal adjustments between a reference video signal and a deteriorated video signal are insufficient, the subjective quality estimating method will be unable to estimate a subjective quality of video images, or even if it is able to do so, the accuracy of the estimation will be poor.
The above-mentioned PCT Pub. No. WO99/45715 discloses, as a document showing an example of a temporal aligning process, ITU-T Contribution COM-12-29, “Draft new recommendation on multimedia communication delay, synchronization, and frame rate measurement,” December 1997.